Zhurnal Radioelektroniki - Journal of Radio Electronics. eISSN 1684-1719. 2020. No. 12
Contents

Full text in Russian (pdf)

Russian page

 

DOI https://doi.org/10.30898/1684-1719.2020.12.19

UDC 621.391.8

 

Time correlation techniques for subsample time delay estimation of complex signals based on polynomial interpolation

 

O. A. Guschina, T. Ya. Shevgunov

Moscow Aviation Institute (National Research University), Volokolamskoe shosse, 4, Moscow, 125993, Russia


The paper was received on December 16, 2020

 

Àííîòàöèÿ. This paper deals with the problem of subsample time delay estimation of complex signal based on polynomial interpolation. Time delay estimation is performed by cross-correlation time approach. Three polynomial interpolation techniques applied to the discrete complex cross-correlation function in the neighborhood of its maximum are proposed. These methods show high processing speed and allow obtaining accurate real-valued time delay estimation when digital complex signals are processed. The comparative analysis between these methods is performed. A rigorous analytical solution for the correction of time delay estimation for one of the proposed methods is obtained for the case of the third-order polynomial interpolation. This solution is applied for an equidistant grid of discrete cross-correlation function samples. One can improve the accuracy of time delay estimates by using aforementioned correction. A numerical simulation is performed to quantify the accuracy of the time delay estimates when using the proposed methods for the case where a stationary random process described by the first-order autoregressive mode is chosen as a model of original signal. The main results were presented and discussed at XIV All-Russian conference “Radar and telecommunication”.

Key words: time delay, crosscorrelation function, polynomial interpolation, mean square error, digital signal processing.

References

1. Dobychina E.M., Malakhov R.Y. Digital antenna arrays for airborne radar system.  Nauchnyi vestnik MGTU GA – Scientific Bulletin of the Moscow State Technical University of Civil Aviation. 2012. No.186. P.176-183. (In Russian)

2. Dobychina E.M. Digital antenna array calibration. Antenny. Radiotekhnika - Antennas. Radio engineering. 2013. No.9. P.46-55. (In Russian)

3. Awad S., Al-Abed M., Saraira A.A. A Comparison of Time Delay Estimation Methods and Interpolation Methods in Signal-Averaged ECG: Preliminary Results. IEEE Jordan International Joint Conference on Electrical Engineering and Information Technology. 2019. P. 371-374. https://doi.org/10.1109/JEEIT.2019.8717446.

4. Sumino Y., Waag R.C. Measurement of ultrasonic pulse arrival time differences produced by abdominal wall specimens. Journal of the Acoustical Society of America. 1991. No.90. P.2924-2930. https://doi.org/10.1121/1.401766

5. Torrieri D. J. Statistical Theory of Passive Location Systems. IEEE Transactions on Aerospace and Electronic Systems. 1984. Vol.AES-20. No.2. P.183-198. https://doi.org/10.1109/TAES.1984.310439.

6. Zekavat R., Buehrer Z. Handbook of Position Location: Theory, Practice, and Advances. IEEE Press. 2017. 1222 p.

7. Efimov E.N., Shevgunov T.Y. Time delay estimation of cyclostationary signals.  Gagarinskie chteniya 2017 [Gagarin Readings 2017]. 2017. P. 621-622. (In Russian)

8. Shevgunov T.Y., Efimov E.N., Zhukov D.M. Cyclostationary random processes applications in digital signal processing problems. DSPA: Voprosy primeneniya tsifrovoi obrabotki signalov - DSPA: Digital Signal Processing Applications. 2018. Vol.8. No.1. P. 152-156. (In Russian)

9. Shevgunov T.Y. Symmetric and general forms of two-dimensional correlation function and cyclic correlation function of non-stationary random processes. Radiotekhnika - Radio Engineering. 2019. No.3. P.33-38. (In Russian)

10. Knapp C., Carter G. The generalized correlation method for estimation of time delay. IEEE Transactions on Acoustics, Speech, and Signal Processing. 1976. Vol.24. No 4. P 320-327. https://doi.org/10.1109/TASSP.1976.1162830.

11. Roth R.R. Effective measurements using digital signal analysis. IEEE Spectrum. 1971. Vol 8. No 4. P 62–70.

12. Dubrovin A.V., Sosulin Y.G. One-step estimation of position location by a passive system. Journal of Communications Technology and Electronics. 1998. Vol.43. No.12. P. 1388-1396.

13. Dubrovin A.V., Sosulin Y.G. One-stage estimation of the position of a radio source by a passive system consisting of narrow-base subsystems. Journal of Communications Technology and Electronics. 2004. Vol.49. No.2. P.139-153.

14. Dubrovin A.V., Sosulin Y.G. One-step estimation of the position of a radio source by a combined passive system. Journal of Communications Technology and Electronics 2007. Vol.52. No.4. P 415-430.    https://doi.org/10.1134/S1064226907040079

15. Zhukov D.M., Vavilova Z.A., Shevgunov T.Y., Guschina O.A., Efimov E.N. An algorithm of global maximum search for evaluating position estimation of electromagnetic emitting source by a passive radar system. Zhurnal radioelektroniki - Journal of Radio Electronics. 2018. No.12. https://doi.org/10.30898/1684-1719.2018.12.8

16. Kumar A., Bar-Shalom Y. Time-domain analysis of cross correlation for time delay estimation with an autocorrelated signal. IEEE Transactions on Signal Processing. 1993. Vol.41. No.4. P.1664–1668. https://doi.org/10.1109/78.212738.

17. Azaria M., Hertz D. Time delay estimation by generalized cross correlation methods. IEEE Transactions on Acoustics, Speech, and Signal Processing. 1984. Vol.32. No.2. P.280-285. https://doi.org/10.1109/TASSP.1984.1164314.

18. Jacovitti G., Scarano G. Discrete time techniques for time delay estimation. IEEE Transactions on Signal Processing. 1993. Vol.41. No.2. P.525-533. https://doi.org/10.1109/78.193195.

19. Cespedes I., Huang Y., Ophir J., Spratt S., Methods of subsample time delays of digitized echo signals. Ultrasonic Imaging. 1995. Vol.17. P.142–171. https://doi.org/10.1177/016173469501700204.

20. Boucher R., Hassab J. Analysis of discrete implementation of generalized cross correlator. IEEE Transactions on Acoustics, Speech, and Signal Processing. 1981. Vol.29. No.3. P. 609-611. https://doi.org/10.1109/TASSP.1981.1163623.

21. Gardner W. A. Introduction to Random Processes. Mcgraw-Hill. 1990. 546 p.

22. Oppenheim A.V., Schafer R.W. Discrete-Time Signal Processing, 3rd ed. Pearson. 2010.

23. Stein S. Algorithms for ambiguity function processing. IEEE Transaction on Acoustics, Speech, and Signal Processing. 1981. Vol.29. No.3. P.588–599. https://doi.org/10.1109/TASSP.1981.1163621.

24. Lindgren G., Rootzen H., Sandsten M. Stationary Stochastic Processes for Scientists and Engineers. CRC Press. 2014. 314 p.

25. Kay S.M. Fundamentals of Statistical Signal Processing: Estimation Theory. Prentice Hall. 1993. 595 p.

26. Bendat J.S, Piersol A.G. Random Data Analysis and Measurement Procedures. Wiley. 2010. 604 p.

27. Gushchina O.A., Shevgunov T.Ya. Application of polynomial approximations to refine the estimate of the delay time of a complex signal in the time domain. XIV All-Russian Scientific and technical Conference “Radiolokatsiya i radiosvyaz'” [“Radar and Radio Communication”]. Moscow, Kotel’nikov IRE RAS. 2020. P.214–219 (In Russian)

  

For citation:

Guschina O.A., Shevgunov T.Ya. Time correlation techniques for subsample time delay estimation of complex signals based on polynomial interpolation. Zhurnal Radioelektroniki - Journal of Radio Electronics. 2020. No.12. https://doi.org/10.30898/1684-1719.2020.12.19  (In Russian)